Two longitudinal regression models, one parametric and one nonparametric, are developed to reduce selection bias when analyzing longitudinal health data with high mortality rates. The parametric mixed model is a two-step linear regression approach, whereas the nonparametric mixed-effects regression model uses a retransformation method to handle random errors across time.
Liu, Xian; Engel, Charles C.; Kang, Han; and Gore, Kristie L.
"Reducing Selection Bias in Analyzing Longitudinal Health Data with High Mortality Rates,"
Journal of Modern Applied Statistical Methods:
2, Article 9.
Available at: http://digitalcommons.wayne.edu/jmasm/vol9/iss2/9